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        "description": "# Korhal\n[![GitHub tag (latest SemVer)](https://img.shields.io/github/tag/ingtranet/korhal.svg?style=flat-square)](https://github.com/ingtranet/korhal)\n[![PyPI](https://img.shields.io/pypi/v/korhal.svg?style=flat-square)](https://pypi.org/project/korhal/)\n[![Travis (.com) branch](https://img.shields.io/travis/com/ingtranet/korhal/master.svg?style=flat-square)](https://travis-ci.com/ingtranet/korhal)\n[![Codacy branch grade](https://img.shields.io/codacy/grade/b8ad24518efb4bec9a68b32eeb994d78/master.svg?style=flat-square)](https://app.codacy.com/project/cookieshake/korhal/dashboard)\n\nKorhal(KOrean Rpc-based Handy Application for Language-processing) is a python wrapper for several korean Part-Of-Speech taggers.\n\n## How to install\n\n``` sh\npip install korhal\n```\n\n## Available taggers\n\n- KOMORAN with `korhal.komoran`\n- Hannanum with `korhal.hannanum`\n- Open-source Korean Text Processor with `korhal.openkoreantext`\n\n## How to use\n\n``` python\nfrom korhal.komoran import tokenize\n\nresult = tokenize(\"\uc9d1\uc5d0 \uac00\uc11c \uc7a0\uc744 \uc790\uace0 \uc2f6\ub2e4\")\n# result => Token(text=\uc9d1,pos=NNG), Token(text=\uc5d0,pos=JKB), Token(text=\uac00,pos=VV), Token(text=\uc544\uc11c,pos=EC), Token(text=\uc7a0,pos=NNG), Token(text=\uc744,pos=JKO), Token(text=\uc790,pos=VV), Token(text=\uace0,pos=EC), Token(text=\uc2f6,pos=VX), Token(text=\ub2e4,pos=EC)]\nprint(result.text) # => \uc9d1\nprint(result.pos) # => NNG\n\nnouns = [token.text for token in result if token.pos.startswith('N')]\n```\n\n## Asynchronous methods\n\nWith `korhal.aio`, you can use asynchronous methods. The performance of multi-core systems can be slightly improved when performing extensive processing.\n\n``` python\nfrom korhal.aio.opentextkorean import tokenize\n\u00a0\ntexts = ['\ub2ec\ub514\ub2e8 \ub9db\uc788\ub294 \ucf00\uc774\ud06c\uac00 \uc788\uc5c8\ub2e4', '\uc19c\uc0ac\ud0d5 \uac19\uc774 \uadc0\uc5ec\uc6b4 \uad6c\ub984']\nfutures = [tokenize(text) for text in texts]\nresults = [f.result() for f in futures]\n```\n\n## Thanks to\n\n- [KOMORAN](http://www.shineware.co.kr/products/komoran/)\n- [Hannanum](http://semanticweb.kaist.ac.kr/hannanum/index.html)\n- [Open-source Korean Text Processor](https://github.com/open-korean-text/open-korean-text)\n- [KoalaNLP](https://koalanlp.github.io/KoalaNLP-core/)",
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